Voriconazole: A Review of Population Pharmacokinetic Analyses 2019-05-08¢  Population Pharmacokinetics

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  • Vol.:(0123456789)

    Clinical Pharmacokinetics (2019) 58:687–703 https://doi.org/10.1007/s40262-019-00735-7

    REVIEW ARTICLE

    Voriconazole: A Review of Population Pharmacokinetic Analyses

    Changcheng Shi1 · Yubo Xiao2 · Yong Mao1 · Jing Wu3 · Nengming Lin4

    Published online: 28 January 2019 © The Author(s) 2019

    Abstract Numerous population pharmacokinetic studies on voriconazole have been conducted in recent years. This review aimed to comprehensively summarize the population pharmacokinetic models for voriconazole and to determine which covariates have been identified and which remain to be explored. We searched the PubMed and EMBASE databases from inception to March 2018 for population pharmacokinetic analyses of voriconazole using the nonlinear mixed-effect method. A total of 16 studies were included in this review, of which 11 models were described in adult populations, four were described in pediatric populations, and the remaining study included both adult and pediatric populations. The absorption profiles of voriconazole in both adult and pediatric studies were best described as first-order absorption models. The typical distribution volumes were similar in adult and pediatric patients, but the estimated clearances in pediatric patients were significantly higher than those in adult patients. The most commonly identified covariates were body weight, the cytochrome P450 2C19 genotype, liver function, and concomitant medications. Only one study evaluated the model using an external method. Further population pharmacokinetic studies on pediatric patients aged younger than 2 years are warranted. Furthermore, new or controversial potential covariates, such as inflammation, the cytochrome P450 3A4 genotype, concomitant medications (particularly various types and dosages of proton pump inhibitors and glucocorticoids), and various measures of body weight, should be tested because the unexplained variability remains relatively high. In addition, previously published models should be externally evaluated, and the predictive performance of the various models should be compared.

    Key Points

    The final structural population pharmacokinetic mod- els of voriconazole differ between adult and pediatric populations.

    Potential and controversial covariates, such as inflamma- tion, the cytochrome P450 3A4 genotype, concomitant medications, and various measures of body weight, should be tested in future studies because the unex- plained variability remains relatively high.

    Previously published models should be externally evalu- ated, and the predictive performances of the models should be compared.

    1 Introduction

    Voriconazole is a new-generation triazole antifungal agent with potent activity against a wide range of clinically sig- nificant pathogens, including Aspergillus and Candida, as

    Changcheng Shi and Yubo Xiao contributed equally to this work and should be considered co-first authors.

    * Nengming Lin lnm1013@163.com

    1 Department of Clinical Pharmacy, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China

    2 Department of Pharmacometrics, Mosim Co., Ltd, Shanghai, China

    3 Department of Pharmacy, Zhejiang Pharmaceutical College, Ningbo, China

    4 Department of Clinical Pharmacology, Translational Medicine Research Center, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, No. 261 Huansha Road, Hangzhou 310006, China

    http://crossmark.crossref.org/dialog/?doi=10.1007/s40262-019-00735-7&domain=pdf

  • 688 C. Shi et al.

    well as some less common fungal pathogens [1]. Since its approval in 2002, voriconazole has changed the approach to the management of invasive fungal diseases. The Infectious Diseases Society of America guidelines now recommend voriconazole as the first-line drug for the treatment of inva- sive aspergillosis and as an alternative drug for the treatment of candidemia [2, 3].

    In recent years, numerous studies have investigated the exposure–response relationship of voriconazole. The find- ings from these studies established that low concentrations might result in higher rates of treatment failure, whereas higher concentrations are associated with increased toxicity; thus, the results identify a narrow target trough concentra- tion range for voriconazole [4, 5]. Furthermore, the wide inter- and intraindividual pharmacokinetic variability is of great concern.

    Several factors are reportedly associated with the large variability in the exposure to conventional doses of vori- conazole, and these include the nonlinear pharmacokinetic properties of voriconazole, the cytochrome P450 (CYP) 2C19 genotype, hepatic dysfunction, and drug interactions [6]. Therapeutic drug monitoring (TDM) for voriconazole is recommended for the optimizing outcomes and reducing toxicity in clinical practice [7]. However, the TDM method can be implemented only after treatment has been initi- ated, and the samples for TDM are traditionally procured at steady state. In fact, steady-state trough concentrations are reached approximately 5 days after standard administra- tion. Although the steady state can be reached 24 h after the administration of a loading dose, a waiting time is still needed and might contribute to a worse prognosis [6]. There- fore, the identification of factors that contribute to the high variability in voriconazole pharmacokinetics is important for determining the appropriate dosage as early as possible.

    Population pharmacokinetic modeling is widely used in the field of clinical pharmacology because it helps determine the typical pharmacokinetic parameters of a population and can be used to obtain the sources of pharmacokinetic varia- bility [8]. The integration of the population pharmacokinetic model with the Bayesian forecasting method can help guide dosage adjustments based on a limited number of drug con- centration measurements [9]. Indeed, many population phar- macokinetic studies on voriconazole have been conducted over the last decade. This review provides an overview of the published studies on the population pharmacokinetics of voriconazole. The objective was to provide a systematic comparison of the population pharmacokinetic models pub- lished for voriconazole and to determine which covariates have been identified and which remain to be explored.

    2 Methods

    2.1 Search Strategy

    The PubMed and EMBASE databases were searched from inception to March 2018 using the following search terms: ‘voriconazole’ AND (‘population pharmacokinetic’ OR ‘pharmacometrics’ OR ‘pharmacokinetic model’ OR ‘popPK’ OR ‘pop PK’ OR ‘PPK’ OR ‘nonlinear mixed effect model’ OR ‘NONMEM’). The reference lists of the relevant studies were searched for additional literature.

    2.2 Inclusion/Exclusion Criteria

    We included all described population pharmacokinetic models for voriconazole. The studies needed to meet the following criteria for inclusion in this review: (1) studied populations, pediatric and adult patients or healthy volun- teers; (2) treatment, voriconazole was used as the study drug, regardless of whether it was administered intravenously or orally; and (3) pharmacokinetic analysis, a nonlinear, mixed- effect population pharmacokinetic modeling approach was employed. The following studies were excluded: (1) reviews, methodology articles, and in vitro and animal studies; (2) papers not written in English; and (3) studies that used non- compartmental or nonparametric approaches.

    2.3 Data Extraction

    Two authors independently performed data extraction using a data collection form, and any discrepancies were resolved by discussion. The following variables were recorded from the identified studies: first author, year of publication, num- ber of patients, patient characteristics (age, sex, weight, genotype, and pathology), route of administration, observed voriconazole concentration, method used for voriconazole determination, number of observations, observations per patient, data source, software used for modeling, dosing sim- ulations, structural and statistical model, tested and retained covariates, and model evaluation method. The model evalu- ation methods were divided into three types based on the increasing order of quality: basic internal, advanced internal, and external model evaluation [10].

    3 Results

    The initial database search yielded 152 publications, and after selection, a total of 16 studies involving 1411 partici- pants met the inclusion criteria [11–26]. The population characteristics of the included studies are summarized in

  • 689Population Pharmacokinetics of Voriconazole

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